The primary aim of this R03 proposal is to identify potential biomarkers for the early detection of ovarian cancer using gene expression profiles detectable in circulating plasma RNA. Ovarian cancer has a high mortality, mainly because there is no proven effective method for early detection. Since ovarian cancer is curable when identified early, development of a reliable blood test for early detection would dramatically impact survival. Recently, circulating nucleic acids have been described as an emerging class of molecular tumor markers with potential application in cancer screening. We have preliminary data to suggest that microarray analysis of circulating plasma RNA can be utilized to identify RNA-biomarkers that may be predictive of the presence of ovarian cancer. Our overall hypothesis is that RNA circulating in plasma can be detected, amplified, and subject to genome-wide expression analysis to identify RNA markers that differentiate women with ovarian cancer from healthy controls. We therefore plan to extend our preliminary findings using samples collected as part of a population-based case-control study in the Tampa Bay area. Plasma RNA obtained from 60 women with invasive epithelial ovarian cancer and 40 healthy control women matched to cases based on age, race, menopausal status and county of residence, will be subject to amplification and microarray analysis. Gene expression patterns will be compared between cases and controls using Bayesian regression analysis, and genes predictive of the presence of ovarian cancer will be identified. By comparing these plasma RNA gene expression patterns with data we previously developed using microarray analysis of 120 primary ovarian cancers, we will select a panel of "candidate RNA biomarkers" to be validated using quantitative real-time PCR. We anticipate that findings from the proposed study will provide impetus and justification for a more comprehensive future R01-funded analysis of RNA biomarkers with clinical utility in early ovarian cancer detection. [unreadable] [unreadable] [unreadable]